超完整！QQ图绘制方法大汇总~~

DataCharm

发布于 2022-02-17 15:05:27

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今天这篇推文小编给大家介绍一些QQ图(Quantile-Quantile Plots) 的绘制方法，主要内容如下：

QQ图(Quantile-Quantile Plots)含义简单介绍
QQ图(Quantile-Quantile Plots)绘制方法

QQ图(Quantile-Quantile Plots)含义简单介绍

「含义」：

QQ图是用于验证一组数据是否符合正太分布，或者验证某两组数据是否来自同一分布情况，是一种散点图，通常情况下，其横坐标为标准正态分布的分位数，纵坐标为样本值。要利用QQ图判定测试样本数据是否近似于正态分布，只需看QQ图上的点是否近似地在一条直线附近，更多关于QQ图的含义理解，小伙伴们可自行搜索哈~~。QQ图样例如下(来源于网络)：

QQ图样例参考

这里小编给大家推荐一个比较好的QQ图介绍视频资源，有条件的小伙伴可以看下哈，虽说是英文的，但是说的非常好，地址如下：https://www.youtube.com/watch?v=okjYjClSjOg。接下来，小编就汇总一下QQ图的R和Python绘制教程。

QQ图(Quantile-Quantile Plots)绘制方法

QQ图R绘制教程

「样例一」：ggplot2绘制

library(tidyverse)
library(ggtext)
library(hrbrthemes)
library(wesanderson)
library(LaCroixColoR)
library(RColorBrewer)
library(qqplotr)
library(ggsci)
#构造数据
df <- data.frame(y = rt(200, df = 5))
#可视化绘制
ggplot(df, aes(sample=y))+
  stat_qq(shape=21,fill="gray",size=4,colour="black",stroke=.5) +
  stat_qq_line(color="red") +
  labs(x = "Theoretical Quantiles", y = "Sample Quantiles",
    title = "Example of <span style='color:#D20F26'>ggplot2::stat_qq function</span>",
    subtitle = "processed charts with <span style='color:#1A73E8'>stat_qq()</span>",
    caption = "Visualization by <span style='color:#0057FF'>DataCharm</span>") +
  hrbrthemes::theme_ipsum(base_family = "Roboto Condensed") +
  theme(
    plot.title = element_markdown(hjust = 0.5,vjust = .5,color = "black",
                                  size = 20, margin = margin(t = 1, b = 12)),
    plot.subtitle = element_markdown(hjust = 0,vjust = .5,size=15),
    plot.caption = element_markdown(face = 'bold',size = 12)
      )

Example Of ggplot2::stat_qq()

「样例二」：R-qqplotr包绘制这个R包是专门绘制QQ图的，这里小编简单介绍下常用方法，更多样例和语法请参考R-qqplotr包[1]。详细如下：

library(qqplotr)
set.seed(0)
smp <- data.frame(norm = rnorm(100))
ggplot(data = smp, mapping = aes(sample = norm)) +
    stat_qq_band(alpha=.4) +
    stat_qq_point(shape=21,size=4,fill="gray60",colour="black",stroke=.5) +
    stat_qq_line(color="red") +
    labs(x = "Theoretical Quantiles", y = "Sample Quantiles",
         title = "Example of <span style='color:#D20F26'>qqplotr::stat_qq_point__* function</span>",
         subtitle = "processed charts with <span style='color:#1A73E8'>stat_qq_point__*()</span>",
         caption = "Visualization by <span style='color:#0057FF'>DataCharm</span>"
        ) +
    hrbrthemes::theme_ipsum(base_family = "Roboto Condensed") +
    theme(
    plot.title = element_markdown(hjust = 0.5,vjust = .5,color = "black",
                                  size = 20, margin = margin(t = 1, b = 12)),
    plot.subtitle = element_markdown(hjust = 0,vjust = .5,size=15),
    plot.caption = element_markdown(face = 'bold',size = 12)
      )

Example01 Of qqplotr QQ charts

注意：qqplotr包提供了stat_qq_band() 函数用于绘制区间，使QQ图更加易于理解。

「多类别」：

ggplot(data = smp, mapping = aes(sample = norm)) +
    geom_qq_band(bandType = "ks", mapping = aes(fill = "KS"), alpha = 0.5) +
    geom_qq_band(bandType = "ts", mapping = aes(fill = "TS"), alpha = 0.5) +
    geom_qq_band(bandType = "pointwise", mapping = aes(fill = "Normal"), alpha = 0.3) +
    geom_qq_band(bandType = "boot", mapping = aes(fill = "Bootstrap"), alpha = 0.5) +
    stat_qq_point(shape=21,size=4,fill="gray60",colour="black",stroke=.5) +
    stat_qq_line() +
    labs(x = "Theoretical Quantiles", y = "Sample Quantiles",
         title = "Example of <span style='color:#D20F26'>qqplotr::stat__qq_point__* function</span>",
         subtitle = "processed charts with <span style='color:#1A73E8'>stat__qq_point__*()</span>",
         caption = "Visualization by <span style='color:#0057FF'>DataCharm</span>") +
    ggsci::scale_fill_jco(name="Bandtype") +
    hrbrthemes::theme_ipsum(base_family = "Roboto Condensed") +
    theme(
        plot.title = element_markdown(hjust = 0.5,vjust = .5,color = "black",
                                      size = 20, margin = margin(t = 1, b = 12)),
        plot.subtitle = element_markdown(hjust = 0,vjust = .5,size=15),
        plot.caption = element_markdown(face = 'bold',size = 12),
      )

Example02 Of qqplotr QQ charts

「分面绘制」：

data("barley", package = "lattice")
ggplot(data = barley, mapping = aes(sample = yield, color = site, fill = site)) +
    stat_qq_band(alpha=0.5) +
    stat_qq_line() +
    stat_qq_point() +
    ggsci::scale_color_nejm() +
    ggsci::scale_fill_nejm() +
    facet_wrap(~ site) +
    labs(x = "Theoretical Quantiles", y = "Sample Quantiles", 
         title = "Example of <span style='color:#D20F26'>qqplotr::stat_qq_point__* function</span>",
         subtitle = "processed charts with <span style='color:#1A73E8'>stat__qq_point__*()</span>",
         caption = "Visualization by <span style='color:#0057FF'>DataCharm</span>") +
    hrbrthemes::theme_ipsum(base_family = "Roboto Condensed") +
    theme(
        plot.title = element_markdown(hjust = 0.5,vjust = .5,color = "black",
                                      size = 20, margin = margin(t = 1, b = 12)),
        plot.subtitle = element_markdown(hjust = 0,vjust = .5,size=15),
        plot.caption = element_markdown(face = 'bold',size = 12),
      )

Example03 Of qqplotr QQ charts + facet_wrap()

更多详细例子和绘图参数，小伙伴们可去qqplotr官网进行查询。

QQ图Python绘制教程

Python 绘制QQ图主要借助其用于统计分析的statsmodels库和scipy库，样例如下：

「statsmodels库绘制」：

import numpy as np
import statsmodels.api as sm
import matplotlib.pyplot as plt
plt.rcParams['font.family'] = "Times New Roman"

# 构建数据
test = np.random.normal(0,1, 200)
# 开始绘图
fig,ax = plt.subplots(figsize=(6,5),dpi=100,)
ax.set_facecolor("white")
sm.qqplot(test, line='45',marker='.', markerfacecolor='gray', markeredgecolor='k',markeredgewidth=.5,
          markersize=14,ax=ax)
ax.set_xlim((-3, 3.0))
ax.set_ylim((-3, 3.0))
ax.grid(linestyle="--",linewidth=.5,color="black")
ax.tick_params(direction='in',labelsize=13)
titlefontdict = {"size":17,"color":"k",'family':'Times New Roman'}
ax.set_title('Example Of QQ Plot In Python-Statsmodels Make',titlefontdict,pad=20)
ax.text(.82,.056,'\nVisualization by DataCharm',transform = ax.transAxes,
        ha='center', va='center',fontsize = 10,color='black')

Example Of QQ Plot In Python-Statsmodels Make

注意：sm.qqplot()在绘制QQ图时，其定制化绘制的灵活性较大，可以对散点样式、颜色、大小、粗细等属性进行设置。更多内容可参考：gofplots.qqplot()[2]

「scipy库绘制」：

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy import stats
fig,ax = plt.subplots(figsize=(6,5),dpi=100)
stats.probplot(test, plot=ax)
ax.set_xlim((-3, 3.0))
ax.set_ylim((-3, 3.0))
ax.grid(linestyle="--",linewidth=.5,color="black")
ax.tick_params(direction='in',labelsize=13)
titlefontdict = {"size":17,"color":"k",'family':'Times New Roman'}
ax.set_title('Example Of QQ Plot In Python-scipy Made',titlefontdict,pad=20)
ax.text(.82,.056,'\nVisualization by DataCharm',transform = ax.transAxes,
        ha='center', va='center',fontsize = 10,color='black')
plt.savefig(r'G:\DataCharm\可视化包介绍(绘制)\QQ图绘制\QQ charts in Python-scipy.png',width=6,height=5.5,
            dpi=900,bbox_inches='tight',facecolor='white')